Data Specialist

hace 4 semanas


Xico, México Cimmyt A tiempo completo
About the Role

CIMMYT, a leading international research organization, is seeking a highly skilled Data Specialist to join its team. As a Data Specialist - Agronomic Analytics and Modeling Expert, you will play a critical role in implementing and supporting the organization's data-driven initiatives.

Key Responsibilities
  • Develop and implement best practices and protocols for data cleaning, analysis, and modeling to ensure high-quality data insights.
  • Design and oversee the development of complex statistical models for agronomic data analysis, leveraging machine learning and AI techniques to extract valuable insights from large-scale agricultural datasets.
  • Validate and refine models to ensure accuracy and reliability of results, aligning with international standards and best practices.
  • Lead the development of methodologies for calculating key agricultural Key Performance Indicators (KPIs), including greenhouse gas emissions, soil health indices, and sustainable practice adoption rates.
  • Collaborate with breeding data teams to integrate data-driven insights into agronomic analyses, ensuring seamless communication and alignment.
  • Implement data governance practices to ensure data integrity and security, overseeing the development and maintenance of data pipelines and storage systems.
  • Prepare and present comprehensive reports on analytical findings to stakeholders, developing data visualizations and dashboards to effectively communicate complex information.
  • Collaborate with cross-functional teams to translate analytical insights into actionable recommendations, driving business growth and improvement.
Requirements
  • Ph.D. in Data Science, Statistics, Computer Science, or a related field.
  • Minimum 5 years of experience in leading data science teams, preferably in an agricultural or environmental context.
  • Advanced level of English language proficiency (English test will be administered; candidate must score a minimum of C1 as per CEFR).
  • Strong background in statistical analysis, machine learning, and predictive modeling.
  • Proficiency in programming languages such as R, Python, and SQL.


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